Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system

Carbon Balance and Management

Rachel Riemann⁴  Craig Wayson³  Ralph Dubayah¹  Anu Swantaran¹  Andrew O Finley²  Richard Birdsey³  Kristofer D Johnson³ 

[1] Department of Geographical Sciences, University of Maryland, College Park, Maryland, USA;Departments of Forestry and Geography, Michigan State University, East Lansing, Michigan, USA;USDA Forest Service, Northern Research Station, Newtown Square, Pennsylvania, USA;USDA Forest Service, Northern Research Station, Troy, New York, USA

关键词: Forest inventory and analysis;    LIDAR;    Inter-comparison;    Carbon;    Aboveground biomass;   

Others  :  790402
DOI  :  10.1186/1750-0680-9-3

 received in 2014-02-24, accepted in 2014-04-23,  发布年份 2014

【 摘 要 】

Background

Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland. Allometric model-related errors were also considered.

Results

In areas of medium to dense biomass, the FIA data were valuable for evaluating map accuracy by comparing plot biomass to pixel values. However, at plots that were defined as “nonforest”, FIA plots had limited value because tree data was not collected even though trees may be present. When the FIA data were combined with a previous inventory that included sampling of nonforest plots, 21 to 27% of the total biomass of all trees was accounted for in nonforest conditions, resulting in a more accurate benchmark for comparing to total biomass derived from the LIDAR maps. Allometric model error was relatively small, but there was as much as 31% difference in mean biomass based on local diameter-based equations compared to regional volume-based equations, suggesting that the choice of allometric model is important.

Conclusions

To be successfully integrated with LIDAR, FIA sampling would need to be enhanced to include measurements of all trees in a landscape, not just those on land defined as “forest”. Improved GPS accuracy of plot locations, intensifying data collection in small areas with few FIA plots, and other enhancements are also recommended.

【 授权许可】

   
2014 Johnson et al.; licensee Springer.

【 图 表 】

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